Hussen Niyomdecha, Suchart Chansamran, Somjai Nupueng
This research aims to develop a predictive model for the decision to increase the palm plantation area of palm oil farmers in the Pakpanang basin and nearby areas in Nakhon Si Thammarat province. Using a binary logistics regression method, the samples of 394 oil palm growers in the study area. Data is collected in a random way, proportionately by population in each district. Use simple sampling by the lottery method from existing contacts and collect data with questionnaires as a research tool. The results of the study predicted the decision to increase the palm oil plantation, finding that the variables that affect the model were statistically significant at 0.05, with 2 variants of 27 variables: training and support staff or contacting seedling sources and the palm oil acquisition market. Farmers who are trained in palm oil cultivation tend to decide to increase the palm oil plantation area significantly higher than those who are not heavily trained. Meanwhile, farmers who have help educators or contact seedling sources and the market to buy palm oil are resisting the decision to increase the oil palm plantation area.